Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 117,527
2 South Dakota 105,997
3 Iowa 83,905
4 Wisconsin 83,532
5 Nebraska 80,163
6 Utah 76,907
7 Rhode Island 73,451
8 Idaho 71,904
9 Tennessee 71,795
10 Wyoming 71,461
11 Montana 71,161
12 Illinois 70,114
13 Kansas 69,901
14 Minnesota 69,498
15 Indiana 67,738
16 Arkansas 65,418
17 Nevada 64,942
18 Alabama 64,383
19 Mississippi 63,978
20 Oklahoma 63,624
21 Missouri 62,270
22 Arizona 61,004
23 New Mexico 60,806
24 Louisiana 60,754
25 Alaska 58,960
26 Florida 55,009
27 Texas 54,212
28 Kentucky 53,796
29 Colorado 53,052
30 Georgia 52,424
31 South Carolina 51,872
32 Ohio 51,831
33 Delaware 50,432
34 Michigan 49,198
35 New Jersey 47,863
36 California 45,798
37 Massachusetts 45,691
38 Connecticut 45,657
39 North Carolina 44,640
40 New York 42,770
41 Pennsylvania 42,525
42 Maryland 40,825
43 West Virginia 38,920
44 District of Columbia 36,987
45 Virginia 35,075
46 Puerto Rico 31,232
47 Washington 29,494
48 New Hampshire 25,711
49 Oregon 23,782
50 Hawaii 14,081
51 Maine 13,641
52 Vermont 10,004

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Tennessee 1,456
2 California 1,303
3 Kansas 1,154
4 Alabama 961
5 Indiana 916
6 Utah 912
7 Arkansas 908
8 Nevada 857
9 Oklahoma 822
10 Massachusetts 810
11 Rhode Island 810
12 Mississippi 796
13 Idaho 785
14 New Mexico 785
15 South Dakota 781
16 Arizona 774
17 Pennsylvania 765
18 Ohio 755
19 West Virginia 751
20 Wyoming 745
21 Louisiana 728
22 Georgia 694
23 Connecticut 684
24 Iowa 684
25 Alaska 677
26 Kentucky 675
27 Delaware 673
28 Texas 673
29 North Carolina 663
30 Nebraska 661
31 South Carolina 631
32 Wisconsin 631
33 Missouri 614
34 Illinois 610
35 New Hampshire 592
36 Montana 591
37 Florida 584
38 Colorado 576
39 New York 556
40 New Jersey 519
41 North Dakota 508
42 Washington 460
43 Michigan 458
44 Minnesota 456
45 Virginia 432
46 Maryland 392
47 Maine 391
48 District of Columbia 361
49 Oregon 333
50 Puerto Rico 283
51 Vermont 170
52 Hawaii 93

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,040
2 New York 1,838
3 Massachusetts 1,684
4 North Dakota 1,615
5 Connecticut 1,565
6 Rhode Island 1,533
7 Louisiana 1,504
8 South Dakota 1,503
9 Mississippi 1,462
10 Illinois 1,278
11 Michigan 1,187
12 Iowa 1,093
13 Indiana 1,079
14 Arizona 1,074
15 Pennsylvania 1,067
16 Arkansas 1,040
17 District of Columbia 1,031
18 New Mexico 1,014
19 Florida 949
20 South Carolina 946
21 Georgia 942
22 Maryland 886
23 Nevada 885
24 Texas 883
25 Delaware 877
26 Alabama 876
27 Tennessee 863
28 Minnesota 847
29 Missouri 842
30 Kansas 803
31 Montana 799
32 Wisconsin 796
33 Nebraska 770
34 Colorado 748
35 Idaho 716
36 Ohio 681
37 West Virginia 608
38 Wyoming 606
39 North Carolina 588
40 Kentucky 585
41 California 567
42 Oklahoma 546
43 Virginia 538
44 New Hampshire 469
45 Puerto Rico 417
46 Washington 416
47 Utah 355
48 Oregon 309
49 Alaska 240
50 Maine 209
51 Hawaii 197
52 Vermont 171

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Kansas 26
2 South Dakota 25
3 North Dakota 24
4 New Mexico 19
5 Pennsylvania 19
6 Arizona 17
7 Rhode Island 17
8 Illinois 16
9 Tennessee 16
10 Indiana 14
11 Minnesota 14
12 West Virginia 14
13 Arkansas 13
14 Wyoming 13
15 Iowa 12
16 Michigan 12
17 Nevada 12
18 Wisconsin 12
19 Alabama 11
20 Idaho 11
21 Mississippi 11
22 Missouri 11
23 Colorado 10
24 Connecticut 10
25 Delaware 9
26 Montana 9
27 New Jersey 9
28 Texas 9
29 California 8
30 Kentucky 8
31 Maryland 8
32 Massachusetts 8
33 New Hampshire 8
34 Ohio 8
35 Louisiana 7
36 North Carolina 7
37 Oregon 7
38 South Carolina 7
39 Nebraska 6
40 Oklahoma 6
41 Utah 6
42 New York 5
43 Florida 4
44 Georgia 4
45 Puerto Rico 4
46 Virginia 4
47 District of Columbia 3
48 Maine 3
49 Vermont 3
50 Alaska 1
51 Hawaii 1
52 Washington 1

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 258,208 1 99
Norton Kansas 214,699 2 99
Bon Homme South Dakota 208,520 3 99
Lincoln Arkansas 208,231 4 99
Buffalo South Dakota 206,422 5 99
Davidson Tennessee 86,269 418 86
Richland South Carolina 57,521 1490 52
York South Carolina 46,196 2102 33
Orange California 37,384 2485 20
Pierce Washington 26,963 2799 10

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 7,587 1 99
Jerauld South Dakota 7,452 2 99
Dickey North Dakota 6,568 3 99
Foster North Dakota 5,919 4 99
Gregory South Dakota 5,735 5 99
Richland South Carolina 765 1685 46
Davidson Tennessee 713 1784 43
York South Carolina 587 2032 35
Orange California 546 2104 33
Pierce Washington 337 2547 18

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons